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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nonlinear noise suppression in a high-rate optical channel with phase modulation and dispersion compensation

We have performed a numerical simulation of transmission of optical DP QPSK signals at a rate of 40 Gbaud over a distance of 2000 km. It is shown that a channel with large negative dispersion and preliminary large positive pulse chirping significantly reduces nonlinear distortion and improves the signal quality. To further reduce the probability of recognition error, it is proposed, instead of a negative dispersion fibre, to use compensators with low attenuation. (fibre-optic communication lines)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Microgap breakdown with floating metal rod perturbations

Here, we report the characterization of microgap breakdown with perturbations from a metal rod floating between anode and cathode electrodes. The effects of the metal rod on the electric field distribution and the field enhancement factor are evaluated by numerical simulation and the conformal mapping method, and they indicate that the field emission regime is not reached. The breakdown voltages in the Townsend discharge regime are determined based on the voltage–current characteristics, which are obtained from two-dimensional fluid simulations. It is found that the breakdown characteristics can be significantly modulated by the floating metal rod, and the breakdown curve (breakdown voltage vs the net gap distance) is no longer U-shaped, which deviates from the conventional Paschen's law. The underlying physical mechanisms are related to the electric field enhancement, curved breakdown path, and nonuniform ion flux caused by the electric shielding effect. The results provide insights into breakdown characteristics in microscale discharges, which may promote conventional investigation of simplified clean gaps toward more complex conditions (e.g., with floating microparticles) in miniaturized plasma devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Ion thermal transport in the H-mode edge transport barrier on DIII-D

The power balance ion heat flux in the pedestal region on DIII-D increases and becomes increasingly anomalous (above conventional neoclassical) in experiments with higher temperature and lower density pedestals where the ion collisionality ($v^*_i$) is lowered toward values expected on ITER. Direct measurements of the main-ion temperature are shown to be essential on DIII-D when calculating the ion heat flux due to differences between the temperature of $D^+$ and the more commonly measured $C^{6+}$ impurity ions approaching the separatrix. Neoclassical transport calculations from NEO and non-linear gyrokinetic calculations using CGYRO are consistent with these observations and show that while neoclassical transport plays an important role, the turbulent ion heat flux due to ion scale electrostatic turbulence is significant and can contribute similar or larger ion heat fluxes at lower collisionality. Beam emission spectroscopy and Doppler backscattering measurements in the steep gradient region of the H-mode pedestal reveal increased broadband, long-wavelength ion scale fluctuations for the low $v^*_i$ discharges at the radius where the non-linear CGYRO simulations were run. Taken together, increased fluctuations, power balance calculations, and gyrokinetic simulations show that the above neoclassical ion heat fluxes, including the increases at lower $v^*_i$, are likely due to weakly suppressed ion scale electrostatic turbulence. These new results are based on world first inferred ion and electron heat fluxes in the pedestal region of deuterium plasmas using direct measurements of the deuterium temperature for power balance across ion collisionalities covering an order of magnitude from high $v^*_i$ values of 1.3 down to ITER relevant $v^*_i$ ~0.1.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Fermionic Partial Tomography via Classical Shadows

Here we propose a tomographic protocol for estimating any k-body reduced density matrix (k-RDM) of an n-mode fermionic state, a ubiquitous step in near-term quantum algorithms for simulating many-body physics, chemistry, and materials. Our approach extends the framework of classical shadows, a randomized approach to learning a collection of quantum-state properties, to the fermionic setting. Our sampling protocol uses randomized measurement settings generated by a discrete group of fermionic Gaussian unitaries, implementable with linear-depth circuits. We prove that estimating all k-RDM elements to additive precision ϵ requires on the order of ($^{n}_{k}$)k 3/2 log(n)/ϵ 2 repeated state preparations, which is optimal up to the logarithmic factor. Furthermore, numerical calculations show that our protocol offers a substantial improvement in constant overheads for k ≥ 2, as compared to prior deterministic strategies. We also adapt our method to particle-number symmetry, wherein the additional circuit depth may be halved at the cost of roughly 2–5 times more repetitions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

Quantum Mechanical Enhancement of the Random Dopant Induced Threshold Voltage Fluctuations and Lowering in Sub 0.1 Micron MOSFETs

A detailed study of the influence of quantum effects in the inversion layer on the random dopant induced threshold voltage fluctuations and lowering in sub 0.1 micron MOSFETs has been performed. This has been achieved using a full 3D implementation of the density gradient (DG) formalism incorporated in our previously published 3D 'atomistic' simulation approach. This results in a consistent, fully 3D, quantum mechanical picture which implies not only the vertical inversion layer quantisation but also the lateral confinement effects manifested by current filamentation in the 'valleys' of the random potential fluctuations. We have shown that the net result of including quantum mechanical effects, while considering statistical fluctuations, is an increase in both threshold voltage fluctuations and lowering.

Asenov, Asen↗
DOE OSTI2020

Coarse grained simulation of convectively driven turbulent mixing, transition, and turbulence decay

Accurate predictions with quantifiable uncertainties are essential to many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. Under-resolved computer simulations are typically unavoidable in such applications, and implicit large-eddy simulation (ILES) often becomes the effective strategy. In this work, we focus on assessing ILES initialized with well-characterized 25 6 3 homogeneous isotropic turbulence datasets generated with direct numerical simulation (DNS). ILES solutions based on the LANL xRAGE code are studied as function of resolution for 6 4 3 , 12 8 3 , 25 6 3 , and 51 2 3 grids. ILES performance of new directionally-unsplit high-order numerical hydrodynamics algorithms in xRAGE is examined in this context. Compared to the initial 25 6 3 DNS, we find longer inertial subranges and higher turbulence Reynolds number (Re) for 25 6 3 and 51 2 3 xRAGE — attributed to having linked DNS (Navier–Stokes based) solutions to nominally inviscid (higher Re) Euler based ILES solutions. For fixed 25 6 3 resolution, we find that significantly larger simulated turbulence Re can be achieved with the higher-order unsplit (vs. split) discretizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Measuring and Simulating T1 and T2 for Qubits

Quantum computers perform computations exploiting quantum mechanics to a possible advantage, allowing us to prepare and manipulate states that do not have a classical equivalent. In particular, phenomena like superposition and entanglement may enable quantum computers to outperform their classical counterparts in certain applications. Implementing these useful quantum algorithms is contingent upon building accurate quantum hardware that is not affected by noise. Environmental noise decreases coherence time of qubits, meaning that qubits do not stay in a desired state long enough to carry out a complex computation. To that end, harnessing the full power of quantum computers necessitate characterization of noise sources and how they impact a given quantum system. Often times, T1and T2 are used to quantify noise. In this project, we provide an approach as to how T1 and T2 values are calculated and simulated for quantum systems. In addition, we compare simulated values of T1 and T2 with those of real quantum computer’s measurements. IBMQ Experience, an open source software allowing users to simulate and use real quantum hardware, is used. QuTip, a Python-based toolbox offering quantum simulation tools for open quantum systems, is also used.

Youssef, Rahaf↗
DOE OSTI2022

Toward Addressing the Challenge to Predict the Heat Capacities of RDX and HMX Energetic Materials

Availability of heat capacity as function of pressure and temperature is an essential prerequisite for development of a computational multiscale strategy capable to address the evolution of microstructure and energy release in advanced high energy density materials. In the case of 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) systems as two of the most studied energetic materials, there are substantial gaps in experimental data, with available heat capacities values distributed only in a region close to standard ambient conditions. In this study we demonstrate how these major experimental limitations can be addressed in the case of the RDX and HMX systems based on the combined use of classical and quantum mechanical calculations. We show that by considering ideal gas properties evaluated using quantum mechanical methods, and residual properties obtained from molecular simulations using fully flexible atomistic force field models, excellent agreement can be obtained for the predicted heat capacities to the most recent experimental values. An important advantage of the current computational methodology is that it allows evaluation of both constant-volume and constant-pressure heat capacities for a broad interval of temperatures and pressures, which encompasses solid and liquid phases conditions. In the case of the solid α and γ phases of RDX and the β phase of HMX, the predicted results follow closely both the available experimental data at standard ambient conditions and the results obtained using density functional theory calculations at high pressures, a regime where experimental data are not available. A perspective to expand the current methodology is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Histidine methyltransferase SETD3 methylates structurally diverse histidine mimics in actin

Actin histidine N τ -methylation by histidine methyltransferase SETD3 plays an important role in human biology and diseases. Here, we report integrated synthetic, biocatalytic, biostructural, and computational analyses on human SETD3-catalyzed methylation of actin peptides possessing histidine and its structurally and chemically diverse mimics. Our enzyme assays supported by biostructural analyses demonstrate that SETD3 has a broader substrate scope beyond histidine, including N-nucleophiles on the aromatic and aliphatic side chains. Quantum mechanical/molecular mechanical molecular dynamics and free-energy simulations provide insight into binding geometries and the free energy barrier for the enzymatic methyl transfer to histidine mimics, further supporting experimental data that histidine is the superior SETD3 substrate over its analogs. This work demonstrates that human SETD3 has a potential to catalyze efficient methylation of several histidine mimics, overall providing mechanistic, biocatalytic, and functional insight into actin histidine methylation by SETD3.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Non-local corrections to the typical medium theory of Anderson localization

We use the recently developed finite cluster typical medium approach to study the Anderson localization transition in three dimensions. Applying our method to the box and binary alloy disorder distributions, we find a fast convergence with the cluster size. We demonstrate the importance of the typical medium environment and the non-local spatial correlations for the proper characterization of the localization transition. As the cluster size increases, our typical medium cluster method recovers the correct critical disorder strength for the transition. Our findings highlight the importance of the non-local cluster corrections for capturing the localization behavior of the mobility edge trajectories. Our results demonstrate that the typical medium cluster approach developed here provides a consistent and systematic description of the Anderson localization transition in the framework of the effective medium embedding schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Environmental Contributions to Proton Sharing in Protein Low-Barrier Hydrogen Bonds

Hydrogen bonds (H-bonds) are central to biomolecular structure and dynamics. Although H-bonds are typically characterized by well-defined proton positions, proton delocalization has been proposed to play a role in facilitating enzyme catalysis and allostery in some systems. Experimentally locating protons is difficult, hampering the study of proton mobility in H-bonds. We used neutron crystallography, atomic resolution X-ray bond length analysis, and large quantum mechanics/molecular mechanics-Born–Oppenheimer molecular dynamics (QM/MM-BOMD) simulations to comprehensively characterize the shared proton/deuteron in a Glu–Asp low-barrier hydrogen bond (LBHB) in the bacterial protein YajL that is a conventional H-bond in the homologous disease-associated human protein DJ-1. X-ray bond length analysis of protiated and perdeuterated DJ-1 and YajL shows no significant effect of deuteron substitution on these carboxylic acid-carboxylate H-bonds but does reveal an effect at the active site glutamic acid near a cysteine thiolate. Residues in an H-bonded network that might favor LBHB formation in YajL were interrogated by the mutation of homologous residues in DJ-1. A distal DJ-1 substitution increases proton delocalization in the Glu–Asp H-bond, demonstrating that mutations within extended H-bond networks can modulate proton transfer barriers in carboxylic acid-carboxylate H-bonds. In addition, proton mobility in the H-bond is correlated with dimer-spanning motions in the QM/MM-BOMD simulations of YajL and DJ-1. Our results show that proton delocalization can be tuned using combined bioinformatic, structural, and computational information, opening the possibility of using engineered proton delocalization as a probe of H-bonding environments and as a tool to test hypotheses about LBHB function.

Lin, Jiusheng [University of Nebraska, Lincoln, NE↗
DOE OSTI2021

Density Functional Tight-Binding Simulations Reveal the Presence of Surface Defects on the Quartz (101)–Water Interface

Understanding the structure and reactivity of quartz–water interfaces is critical for numerous applications in the geological, environmental, and biological sciences. However, disagreements on the atomic-level structure of the interfaces between experiments and simulations are hampering our ability to predict the surface reactivity. Here, we used density functional tight-binding (DFTB)-based molecular dynamics to simulate a series of quartz (101) surfaces having different types and densities of surface defects in water and compared them with the structures determined by X-ray reflectivity measurements. The DFTB simulations are able to reproduce previous classical and quantum mechanical predictions of the pristine quartz (101)–water interface that disagree with experimental observations. To remedy this situation, a set of defective quartz surfaces having various surface silicon (Si) vacancies were built as indicated by recent experimental studies. We found that the rotation of surface [SiO 4 ] tetrahedra near Si vacancies can lead to outward displacements of Si atoms similar to those observed in the experiments. The presence of additional surface Si vacancies caused inward relaxations of terminal oxygens through the formation of hydrogen bonds. Finally, the overall results indicate that the quartz (101)–water interface may include a mixture of geminal (≡Si–(OH) 2 )- and vicinal (≡Si–OH)-type silanol groups together with the presence of surface Si vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential

Thermodynamic phase stability of three elemental boron allotropes, i.e., α-B, β-B, and γ-B, was investigated using a Bayesian interatomic potential trained via a sparse Gaussian process (SGP). SGP potentials trained with datasets from on-the-fly active learning achieve quantum mechanical level accuracy when employed in molecular dynamics simulations to predict wide-ranging thermodynamic, structural, and vibrational properties. The simulated phase diagram (500~1400 K and 0~16 GPa) agrees with experimental measurements. The SGP-based MD simulations also successfully predicted that the B13 defect is critical in stabilizing β-B below 700 K. At higher temperatures, the entropy becomes the dominant factor, making β-B the more stable phase over α-B. Furthermore, this Letter demonstrates that SGP potentials based on a training set consisting of defect-free-only systems could make correct predictions of defect-related phenomena in solid-state crystals, paving the path to investigate crystal phase stability and transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Practical quantum computation of chemical and nuclear energy levels using quantum imaginary time evolution and Lanczos algorithms

Various methods have been developed for the quantum computation of the ground and excited states of physical and chemical systems, but many of them require either large numbers of ancilla qubits or high-dimensional optimization in the presence of noise. The quantum imaginary-time evolution (QITE) and quantum Lanczos (QLanczos) methods proposed in Motta et al. (2020) eschew the aforementioned issues. In this study, we demonstrate the practical application of these algorithms to challenging quantum computations of relevance for chemistry and nuclear physics, using the deuteron-binding energy and molecular hydrogen binding and excited state energies as examples. With the correct choice of initial and final states, we show that the number of timesteps in QITE and QLanczos can be reduced significantly, which commensurately simplifies the required quantum circuit and improves compatibility with NISQ devices. We have performed these calculations on cloud-accessible IBM Q quantum computers. With the application of readout-error mitigation and Richardson error extrapolation, we have obtained ground and excited state energies that agree well with exact results obtained from diagonalization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Probing entanglement in a 2D hard-core Bose–Hubbard lattice

Entanglement and its propagation are central to understanding many physical properties of quantum systems. Notably, within closed quantum many-body systems, entanglement is believed to yield emergent thermodynamic behaviour. However, a universal understanding remains challenging owing to the non-integrability and computational intractability of most large-scale quantum systems. Quantum hardware platforms provide a means to study the formation and scaling of entanglement in interacting many-body systems. Here we use a controllable 4 × 4 array of superconducting qubits to emulate a 2D hard-core Bose–Hubbard (HCBH) lattice. We generate superposition states by simultaneously driving all lattice sites and extract correlation lengths and entanglement entropy across its many-body energy spectrum. We observe volume-law entanglement scaling for states at the centre of the spectrum and a crossover to the onset of area-law scaling near its edges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗